A Novel Fixed Pattern Noise Reduction Algorithm in CMOS Detector for LEO Satellite Application

In this paper a novel algorithm for fixed pattern noise reduction in spatial images is discussed. These images are provided by star tracker camera. Star tracker is the most accurate sensor for attitude determination of a satellite by observing stars. The precision of attitude determination depends on the accuracy of the star tracker image registration. Thus the calibration of a fixed pattern noise as a major noise source of the star tracker images has an important role. The FPN is a variation in the output pixel values, under uniform illumination, due to device and interconnection mismatches across an image sensor. In this paper, proposed algorithms based on averaging of these variations and then adapt them to average variations with ideal image. Experimental results and comparison with other famous filters, confirm that the algorithm presented in this paper is able to reduce significant noise level with high speed processing. This algorithm was implemented on an ARM processor with 1GHz clock speed and then it could able to remove FPN from star images in acceptable level less than 5 millisecond.